面谈
Matt Meyers,Lenovo北美SMB公司总经理-访谈系列
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马特·梅耶斯(Matt Meyers)是莱诺沃北美SMB的总经理，他在那里与小型和中型企业合作，导航AI的领养，网络安全，以及现代IT的业务需求。 他在勒诺沃度过了十多年，他的经验涉及全球账户、服务和软件、数字工作场所解决方案以及商业领导。 这一进展决定了他注重帮助较小的组织获得符合其预算和精简的信息技术团队的能力和安全技术。 他的观点集中在实际业务成果上：确定有用的AI应用，将设备和服务与雇员的需求相匹配，并在扩大技术投资之前衡量技术投资的价值。
Lenovo是一家全球技术公司，其投资组合涵盖个人计算、基础设施、软件、解决方案和服务。 其提供的业务包括人工智能个人电脑、数字工作场所解决方案、ThinkShield安全以及基于Truscale的订阅服务。 对于中小型企业来说，这些能力将设备、支持、安全和生命周期管理结合起来，以帮助简化技术业务。 随着AI成为日常业务应用和工作流程的一部分，Lenovo正在开发跨越设备、边缘和云层环境的解决方案，为各组织如何部署和管理技术提供了选择。
你花了十多年的时间在勒诺沃，通过全球账户、服务和软件、数字工作场所解决方案、商业领导，以及现在的北美SMB。 与大型企业相比，这种进步如何改变你对中小型企业面临的技术挑战的看法？
我发现无论公司规模大小，每个组织都在努力提高生产力，加强安全，控制成本，并确定如何利用AI等新的创新创造竞争优势。
在资源方面，SMB是不同的。 大型企业往往设有专注于安全，基础设施，采购，AI和数字化转型的专职团队。 在许多SMB中，这些责任可能落在少数人身上，甚至落在一个人身上。 这给复杂性或失误留下的空间很小。
我所学到的就是SMB不需要规模化的企业技术。 他们需要围绕其运作方式的现实设计解决办法。 技术必须安全、易于部署、易于管理并能够迅速提供价值。 当我们说得对时，技术就成为增长的促进因素，而不是另一个争夺时间和注意力的业务负担。
AI的通过对于一个拥有一个小的IT团队和有限的预算的SMB来说是压倒性的。 企业在开始对AI进行认真投资前，应该先有两三件事是什么？.
我所看到的各组织最大的错误是从技术开始而不是从商业问题开始。
第一步是确定大赦国际可在哪些方面产生可衡量的影响。 这可能包括减少行政工作、提高客户反应能力、帮助雇员更快地获得信息或精简决策。 最强的人工智能举措与具体业务成果挂钩。
第二，了解你的数据。 各组织需要清楚地了解它们拥有哪些信息，信息位于何处，谁可以获得，以及哪些信息绝不应输入公共AI环境中。 在开始前你不需要完美的治理
第三，在进行投资之前界定成功与否。 如果目标是生产力，就确定基线。 如果目标是降低成本，请了解今天的成本。 一种实际做法是从重点使用案例开始，证明价值，然后根据成果而不是假设来进行规模。
从你合作的SMB 客户看，你今天在哪里看到AI产生有形价值，与企业实际取得的结果相比，哪些案例仍然被过度夸大？
最直接的价值在于日常生产力。
我们看到各组织利用AI来总结信息，创建和完善内容，分析文件，表露见解，减少重复的行政工作。 这些任务中没有任何一项可能看起来是变革性的，但集体地在一个组织内产生有意义的增效。
期望有时比现实更早的地方是完全自动化。 仍有人认为AI可以完全取代复杂的角色或业务流程，对今天的多数SMB来说
最强的结果来自使用AI来增强员工，消除工作流程中的摩擦，加快决策。 最好的起点仍然是可重复的、高频的任务，在这些任务中，影响是可衡量的，而且可以迅速采用。
许多公司被鼓励升级为AI个人电脑。 对于一个SMB的拥有者来说，在设备上在当地运行AI能真正带来什么工作量，而常规的PC与基于云的AI结合何时仍然足够？
因为并不是每个员工都一样工作
AI PC为经常依赖AI辅助应用程序，实时转录和翻译，高级协作工具，内容创建工作流程或涉及敏感信息的工作量的用户提供最多价值。 本地AI可以提高响应能力，减少对连接的依赖，并使某些AI功能能够使用专用处理资源直接运行在设备上。 对于一个希望某些信息留在设备上的组织，当地AI可能有用，但取决于其安全政策和使用中的应用。
同时，并不是每个员工今天都需要AI PC. 主要使用传统生产力应用程序和偶尔使用云基人工智能服务的员工可能会继续看到传统系统的强劲业绩。
对话不应该仅仅因为 AI PC 可用，它应当涉及使正确的技术与雇员、工作量和企业的未来需要相匹配。 最有效的技术战略使投资与结果而不是趋势相一致。
Lenovo一直在扩展其AI PC策略，同时通过Truscale提供设备服务模型。 一个较小的公司如何决定购买和管理自己的硬件，或转向以订阅为基础的模式，是否具有更多的财务和业务意义？
我鼓励SMB领导人评价管理技术的财务影响和业务现实。
当设备需求可以预测时，传统所有权就是合理的，本组织有资金进行预先投资，并有资源管理部署、支助、生命周期管理和内部更新规划。
如果目标是每月可预测的费用、灵活性和减少业务负担，则“服务设备”模式就具有吸引力。 Lenovo Truscale DaaS等解决方案将装置和生命周期服务合并为一个订阅模式，帮助各组织简化装置的部署、支持、管理和退役。
最终，问题不只在于公司如何支付技术费用。 问题在于它希望它的人民花在哪里。 对许多SMB来说，真正的价值来自允许内部团队专注于推动增长的战略重点，而不是管理设备生命周期和日常管理。
随着员工获得基因AI工具并可能暴露敏感公司数据，网络安全变得越来越困难。 随着AI被嵌入日常工作流程，SMB应该特别关注什么新的安全风险？
最直接的关切之一是数据暴露。
雇员可以无意中通过人工智能工具分享专有信息、客户数据、金融信息或知识产权，而不完全了解这些信息是如何储存、处理或使用的。 各组织需要围绕核准的人工智能工具和数据处理做法制定明确政策。
同时，AI正在提高网络威胁的精密度。 捉弄运动，冒充企图和社会工程攻击越来越有说服力，更难以识别。
尽管面临这些新的挑战，但基本要素仍然至关重要。 强有力的身份管理、多要素认证、端点保护、定期补丁、后备战略和雇员教育仍然是一些最有效的防御手段。 AI改变威胁面貌
勒诺沃将ThinkShield解决方案定位在内部信息技术资源有限的组织周围。 今天，有多少网络安全可以实际自动化或外包，而SMB从不把哪些安全责任完全移交给第三方？
日常安保业务的相当一部分今天可以自动化或得到信任的伙伴的支持。
通过自动化和管理服务，可以越来越多地提供终端监测、补丁管理、威胁检测和事件应对等能力。 对于SMB来说，这可以提供企业级能力，而不需要企业规模的团队。
ThinkShield是技术如何支持自动化和帮助组织管理安全复杂性的一个例子。 然而，问责制不能外包。
每个组织仍需要了解其最关键的数据，确定谁应该能够利用这些数据，制定政策，确定可接受的风险，并创造一种安全是每个人的责任的文化。 技术和服务提供者可以帮助管理复杂性，但领导必须保持对风险管理、治理和业务决策的所有权。
最强有力的安全战略是以伙伴关系而不是权力下放为基础的。
综合服务可以减轻精干的IT团队的负担，但也可以增加对少数技术提供者的依赖。 SMB如何平衡简单和管理的服务与灵活性、互操作性和供应商锁定等关切问题？
对于大多数SMB来说，简洁具有真正的战略价值。
每个额外的供应商，平台和管理层推出复杂性。 这种复杂性消耗时间，增加业务间接费用，并可能分散有限资源对高价值优先事项的注意力。
称简洁绝不应牺牲灵活性。 各组织应寻找与现有环境充分融合的解决办法，支持开放的生态系统，并允许它们随着业务需求的变化而演变。
我始终鼓励领导人在进程初期询问潜在的技术伙伴关于互操作性、可移植性和灵活性的问题。 最佳技术伙伴关系创造各种选择并减少复杂性。 他们不应该让未来的变革更加困难或昂贵。
大赦国际面临的一个挑战是在投入大量资源之前确定投资收益。 SMB领导人用什么衡量标准来决定AI的部署是实际上在提高生产力还是在降低成本，而不是简单地增加另一个技术层？
最有效的衡量方法也是最简单的：将结果与最初的业务目标挂钩。
如果目标是提高生产力，则衡量节省的时间。 如果目标是改善客户经验，则衡量回应时间，客户满意度和解析率。 如果目标是降低成本，则比较
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Interviews
Matt Meyers, General Manager, North America SMB at Lenovo – Interview Series
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Matt Meyers is General Manager, North America SMB at Lenovo, where he works with small and midsized businesses navigating AI adoption, cybersecurity, and the operational demands of modern IT. He has spent more than a decade at Lenovo, with experience spanning global accounts, services and software, digital workplace solutions, and commercial leadership. That progression has shaped his focus on helping smaller organizations access capable, secure technology that fits their budgets and lean IT teams. His perspective centers on practical business outcomes: identifying useful AI applications, matching devices and services to employee needs, and measuring the value of technology investments before expanding them.
Lenovo is a global technology company whose portfolio spans personal computing, infrastructure, software, solutions, and services. Its business offerings include AI-enabled PCs, digital workplace solutions, ThinkShield security, and TruScale subscription-based services. For small and midsized businesses, these capabilities bring together devices, support, security, and lifecycle management to help simplify technology operations. As AI becomes part of everyday business applications and workflows, Lenovo is developing solutions across devices, edge, and cloud environments, giving organizations options for how they deploy and manage their technology.
You’ve spent more than a decade at Lenovo, moving through global accounts, services and software, digital workplace solutions, commercial leadership, and now North America SMB. How has that progression changed the way you think about the technology challenges facing small and midsized businesses compared with large enterprises?
Throughout my career at Lenovo, I’ve found that the fundamental technology challenges are remarkably consistent regardless of company size. Every organization is trying to improve productivity, strengthen security, control costs and determine how to leverage new innovations such as AI to create competitive advantage.
Where SMBs differ is in resources. Large enterprises often have dedicated teams focused on security, infrastructure, procurement, AI and digital transformation. In many SMBs, those responsibilities may fall to a handful of people, or even a single individual. That leaves very little room for complexity or missteps.
What that has taught me is that SMBs don’t need scaled-down versions of enterprise technology. They need solutions designed around the realities of how they operate. Technology must be secure, easy to deploy, easy to manage and capable of delivering value quickly. When we get that right, technology becomes a growth enabler rather than another operational burden competing for time and attention.
AI adoption can feel overwhelming for an SMB with a small IT team and limited budget. What are the first two or three things a business should have in place before it starts investing seriously in AI?
The biggest mistake I see organizations make is starting with the technology instead of the business problem.
The first step is identifying where AI can create measurable impact. That might be reducing administrative work, improving customer responsiveness, helping employees access information faster, or streamlining decision-making. The strongest AI initiatives are tied to a specific business outcome.
Second, understand your data. Organizations need a clear understanding of what information they have, where it resides, who has access to it and what information should never be entered into public AI environments. You don’t need perfect governance before getting started, but you do need a foundation.
Third, define success before making the investment. If the goal is productivity, establish a baseline. If the goal is cost reduction, understand today’s costs. A practical approach is to start with focused use cases, prove value and then scale based on results rather than assumptions.
From the SMB customers you work with, where are you seeing AI generate tangible value today, and which use cases are still being overhyped relative to the results businesses are actually achieving?
The most immediate value is in everyday productivity.
We are seeing organizations use AI to summarize information, create and refine content, analyze documents, surface insights and reduce repetitive administrative work. None of those tasks individually may seem transformative, but collectively they create meaningful efficiency gains across an organization.
Where expectations are sometimes ahead of reality is around complete automation. There’s still a perception that AI can fully replace complex roles or business processes with minimal oversight. For most SMBs today, that’s not where the greatest value is being realized.
The strongest results come from using AI to augment employees, remove friction from workflows and accelerate decision-making. The best starting point remains repeatable, high-frequency tasks where the impact is measurable and adoption can happen quickly.
Many companies are being encouraged to upgrade to AI PCs. For an SMB owner, what workloads genuinely benefit from running AI locally on the device, and when does a conventional PC combined with cloud-based AI remain sufficient?
There isn’t a universal answer because not every employee works the same way.
AI PCs deliver the most value for users who regularly rely on AI-enabled applications, real-time transcription and translation, advanced collaboration tools, content creation workflows or workloads involving sensitive information. Local AI can improve responsiveness, reduce reliance on connectivity and enable certain AI functions to run directly on the device using dedicated processing resources. For an organization that wants certain information to remain on the device, local AI may be useful, subject to its security policies and the application in use.
At the same time, not every employee requires an AI PC today. Employees primarily using traditional productivity applications and occasional cloud-based AI services may continue to see strong performance from conventional systems.
The conversation shouldn’t be about refreshing devices simply because AI PCs are available. It should be about matching the right technology to the employee, the workload and the future needs of the business. The most effective technology strategies align investments with outcomes rather than trends.
Lenovo has been expanding its AI PC strategy while also offering Device-as-a-Service models through TruScale. How can a smaller company determine whether buying and managing its own hardware or moving toward a subscription-based model makes more financial and operational sense?
I encourage SMB leaders to evaluate both the financial impact and the operational reality of managing technology.
Traditional ownership can make sense when device requirements are predictable, the organization has capital available for an upfront investment and it has the resources to manage deployment, support, lifecycle management and refresh planning internally.
A Device-as-a-Service model can be attractive when the goal is predictable monthly costs, flexibility and reducing operational burden. Solutions such as Lenovo TruScale DaaS combine devices and lifecycle services into a subscription model, helping organizations simplify deployment, support, management and retirement of devices.
Ultimately, the question isn’t just how a company wants to pay for technology. The question is where it wants its people spending their time. For many SMBs, the real value comes from allowing internal teams to focus on strategic priorities that drive growth rather than managing device lifecycles and day-to-day administration.
Cybersecurity is becoming more difficult as employees gain access to generative AI tools and potentially expose sensitive company data. What new security risks should SMBs be paying particular attention to as AI becomes embedded in everyday workflows?
One of the most immediate concerns is data exposure.
Employees can unintentionally share proprietary information, customer data, financial information or intellectual property through AI tools without fully understanding how that information is stored, processed or used. Organizations need clear policies around approved AI tools and data handling practices.
At the same time, AI is increasing the sophistication of cyber threats. Phishing campaigns, impersonation attempts and social engineering attacks are becoming more convincing and more difficult to identify.
Despite these new challenges, the fundamentals remain critically important. Strong identity management, multifactor authentication, endpoint protection, regular patching, backup strategies and employee education continue to be some of the most effective defenses available. AI changes the threat landscape, but it doesn’t change the importance of strong cybersecurity discipline.
Lenovo has positioned ThinkShield solutions around organizations with limited internal IT resources. How much of cybersecurity can realistically be automated or outsourced today, and which security responsibilities should an SMB never completely hand over to a third party?
A significant portion of day-to-day security operations can be automated or supported by trusted partners today.
Capabilities such as endpoint monitoring, patch management, threat detection and incident response can increasingly be delivered through automation and managed services. For SMBs, that can provide access to enterprise-grade capabilities without requiring enterprise-sized teams.
ThinkShield is one example of how technology can support automation and help organizations manage security complexity. However, accountability cannot be outsourced.
Every organization still needs to understand its most critical data, determine who should have access to it, establish policies, define acceptable risk and create a culture where security is everyone’s responsibility. Technology and service providers can help manage complexity, but leadership must maintain ownership of risk management, governance and business decisions.
The strongest security strategies are built on partnership, not delegation.
Integrated services can reduce the burden on lean IT teams, but they can also increase reliance on a small number of technology providers. How should SMBs balance simplicity and managed services against concerns such as flexibility, interoperability, and vendor lock-in?
For most SMBs, simplicity has real strategic value.
Every additional vendor, platform and management layer introduces complexity. That complexity consumes time, increases operational overhead and can distract limited resources from higher-value priorities.
That said, simplicity should never come at the expense of flexibility. Organizations should look for solutions that integrate well with their existing environments, support open ecosystems and allow them to evolve as business requirements change.
I always encourage leaders to ask potential technology partners about interoperability, portability and flexibility early in the process. The best technology partnerships create options and reduce complexity. They shouldn’t make future change more difficult or expensive.
One challenge with AI is determining return on investment before committing significant resources. What metrics should SMB leaders use to decide whether an AI deployment is actually improving productivity or reducing costs rather than simply adding another technology layer?
The most effective measurement approach is also the simplest: tie outcomes back to the original business objective.
If the goal is improving productivity, measure time saved. If the goal is improving customer experience, measure response times, customer satisfaction and resolution rates. If the objective is cost reduction, compare the pro
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